LipsLev
PyTorch implementation of certified robustness against bounded Levenshtein distance edits.
PyTorch implementation of certified robustness against bounded Levenshtein (edit) distance perturbations from the ICLR 2025 paper. Provides Lipschitz-constrained text classifiers with formal robustness certificates, training scripts, verification methods, and pre-trained models. Also covers the related Charmer method.
Natural LanguagePyTorchRobustness
- Technical
- Source code: Lab Github
- Last commit: 2025-02-19
Laboratory for Information and Inference Systems
Laboratory for Information and Inference Systems
At LIONS, we are concerned with optimized information extraction from signals or data volumes. We therefore develop mathematical theory and computational methods for information recovery from highly incomplete data.
This page was last edited on 2026-03-03.
This page was last edited on 2026-03-03.